Confusion Matrix
Confusion Matrix in Machine Learning 1. Introduction to Confusion Matrix A Confusion Matrix is a performance evaluation metric used in classification problems. It helps to understand how well a machine….
Tag: Model Evaluation
ROC Curve and AUC
ROC Curve and AUC in Machine Learning The ROC (Receiver Operating Characteristic) Curve and AUC (Area Under the Curve) are essential metrics for evaluating the performance of classification models, especially….
Train-Test Split and Cross-Validation
Train-Test Split and Cross-Validation in Machine Learning In machine learning, evaluating the performance of a model is crucial to ensure it generalizes well to unseen data. Two widely used techniques….
Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
Types of Machine Learning Machine Learning (ML) is classified into three main types: Each type has its own approach, methodologies, and applications. Below, we will explore them in detail, covering….
Imbalanced Data Handling
Handling Imbalanced Data in Machine Learning Introduction Imbalanced data occurs when the distribution of classes in a dataset is highly skewed, meaning one class has significantly more samples than the….
The Data Science Workflow
The Data Science Workflow: A Detailed Guide The Data Science Workflow is a structured process that guides data scientists through solving problems using data. It involves several key stages, from….